8 citations · 10 across the 4 of their papers we have counts for
5 papers
Equality of Effort via Algorithmic Recourse
Francesca E. D. Raimondi, Andrew R. Lawrence, Hana Chockler
This paper proposes a method for measuring fairness through equality of effort by applying algorithmic recourse through minimal interventions. Equality of effort is a property that…
Causal Analysis of the TOPCAT Trial: Spironolactone for Preserved Cardiac Function Heart Failure
Francesca E. D. Raimondi, Tadhg O'Keeffe, Hana Chockler +6
We describe the results of applying causal discovery methods on the data from a multi-site clinical trial, on the Treatment of Preserved Cardiac Function Heart Failure with an Aldo…
Domain Knowledge in A*-Based Causal Discovery
Steven Kleinegesse, Andrew R. Lawrence, Hana Chockler
Causal discovery has become a vital tool for scientists and practitioners wanting to discover causal relationships from observational data. While most previous approaches to causal…
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data
Andrew R. Lawrence, Marcus Kaiser, Rui Sampaio +1
Going beyond correlations, the understanding and identification of causal relationships in observational time series, an important subfield of Causal Discovery, poses a major chall…
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
Andrew R. Lawrence, Carl Henrik Ek, Neill D. F. Campbell
We present a non-parametric Bayesian latent variable model capable of learning dependency structures across dimensions in a multivariate setting. Our approach is based on flexible…